ABSTRACT
[This corrects the article DOI: 10.1017/ash.2021.254.].
ABSTRACT
While basically all countries have been hit by the COVID-19 pandemic, the impact has varied in large degrees among countries. In the present study, national differences in six COVID-19 indicators (COVID-19 deaths per capita, excess mortality, change in GDP per capita, vaccination rate, stringency index, and overall impact of the pandemic) were studied in relation to socio-economic and Hofstede's cultural dimensions by using the latest data available. The results differed to some degree from the studies conducted in the earlier stage of the pandemic. COVID-19 deaths per capita were predicted by Uncertainty Avoidance (UA) and Indulgence (IVR); excess mortality by UA; the impact of pandemics by Power Distance (PDI), Long-term Orientation (LTOWS) and IVR; change in GDP per capita by PDI; vaccination rate by Individualism and UA; and Stringency Index by LTOWS. In addition to further clarifying the role of cultural dimensions in the pandemic, three conclusions can be drawn. First, the pandemic reached different countries at different times, which is reflected in the results. The conclusion about the role of socio-economic and cultural factors can be drawn only after the pandemic. Second, cultural dimensions were related to COVID-19 measures only when socio-economic indicators were not considered but lost their significance when socio-economic variables were entered into the models. Cultural dimensions influence the outcome variables via socio-economic factors. Third, earlier studies have focused mainly on COVID-19 deaths. The impact of the COVID-19 pandemic is a complex phenomenon and cannot be reduced to the death rate.
Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Humans , PandemicsABSTRACT
Objectives: In this study, we sought to determine the prevalence of bloodstream infection (BSI) in severe coronavirus disease 2019 (COVID-19) patients and to determine the risk factors of BSI in critical COVID-19 patients. Design: Retrospective, descriptive study between March 2020 and January 2021. Setting: An 1,007-bed university hospital. Participants: Patients who were hospitalized due to severe COVID-19 disease and had an aerobic blood culture taken at least once during hospitalization. Methods: Case definitions were made according to National Institutes of Health clinical definitions. According to the blood culture results, the patients were grouped as with and without BSIs, and compared for BSIs risk factors. Results: In total, 195 patients were included in the study. Blood culture positivity was detected in 76 (39.0%) of 196 patients. Excluding blood culture positivity considered as contamination, the prevalence of BSI in all severe COVID-19 cases was 18.5% (n = 36). In intensive care unit patients the prevalence of BSI was 30.6% (n = 26). In multivariate analyses, central venous catheter (odds ratio [OR], 8.17; 95% confidence interval [CI], 2.46-27.1; P < .01) and hospitalization in the multibed intensive care unit (OR, 4.28; 95% CI, 1.28-14.3; P < .01) were risk factors associated with the acquisition of BSI. Conclusion: The prevalence of BSI in COVID-19 patients is particularly high in critically ill patients. The central venous catheter and multibed intensive care follow-up are risk factors for BSI. BSIs can be reduced by increasing compliance to infection control measures and central venous catheter insertion-care procedures. The use of single-bed intensive care units where compliance can be achieved more effectively is important for the prevention of BSIs.
ABSTRACT
Background/aim: Pneumonia is the most serious clinical presentation of COVID-19. This study aimed to determine the demographic, clinical, and laboratory findings that can properly predict COVID-19 pneumonia. Materials and methods: This study was conducted in the Gazi University hospital. All hospitalized patients with confirmed and suspected SARS-CoV-2 infection between 16 March 2020 and 30 April 2020 were analyzed retrospectively. COVID-19 patients were separated into two groups, pneumonia and nonpneumonia, and then compared to determine predicting factors for COVID-19 pneumonia. Variables that had a P-value of less than 0.20 and were not correlated with each other were included in the logistic regression model. Results: Of the 247 patients included in the study 58% were female, and the median age was 40. COVID-19 was confirmed in 70.9% of these patients. Among the confirmed COVID-19 cases, 21.4% had pneumonia. In the multivariate analysis male sex (P = 0.028), hypertension (P = 0.022), and shortness of breath on hospital admission (P = 0.025) were significant factors predicting COVID-19 pneumonia. Conclusion: Shortness of breath, male sex, and hypertension were significant for predicting COVID-19 pneumonia on admission. Patients with these factors should be evaluated more carefully for diagnostic procedures, such as thorax CT.